CAV Systems Incorporating Air Pollution Information from Traffic Congestion

Principal Investigator(s):

Krishnakumar Nedunuri, Professor of Environmental Engineering – Central State University
Director – C.J. McLin International Center for Water Resources Management
Ramanitharan Kandiah, Professor of Environmental Engineering & Program Coordinator – Central State University
Deng Cao, Associate Professor of Computer Science – Central State University

Project Abstract:
Through the CCAT center, CSU proposes to study air pollutants under different traffic congestion scenarios along selected freeways in Ohio. The study captures pollution intensities in different seasons of the year representing different atmospheric stabilities and concentration of criteria air pollutants and greenhouse gases as a function of hold-up times and traffic densities. Our prior work has determined typical hot spots in Ohio along freeways that are prone to high traffic densities and possible congestion. MOVES will be used to generate these scenarios to determine emissions from vehicles in a simulated traffic congestion scenario across interstate intersections. ODOT traffic data will be used for these scenarios. The resulting air pollutants and greenhouse gases from emissions will be determined using a dispersion model. Concentrations of the air pollutants will be compared with NAAQS. A model will be developed to assess the severity of air pollution and calibrated using emission measurements from the Engine Exhaust Analyzer. It will be used to forecast the air quality index for the congested areas (primarily interstate intersections) on freeways. CAV technology will then be deployed to communicate the information to travelers on freeways on radio channels approaching these congested areas.

Institution(s): Central State University

Award Year: 2018

Research Thrust(s): Enabling Technology, Modeling & Implementation

Project Form(s):